System for determining an illegitimate three dimensional video and methods thereof

ABSTRACT

A method, non-transitory computer readable medium, and video analyzing computing device that generates a scene averaged frame value for each scene of an original video and a each scene of a resembling video. Each of a subset of the scenes of the resembling video is mapped to a corresponding scene of the original video based on a comparison of the scene averaged frame values. A singular value score is generated for each frame of each of the subset of scenes of the resembling video and each frame of the corresponding one of the scenes of the original video is generated. Matching one(s) of the one or more frames of each of the at least a subset of scenes of the resembling video is identified based on a comparison of at least a subset of the singular value scores. A first watermark is extracted from the identified matching frames.

This application claims the benefit of Indian Patent Application No.5744/CHE/2013 filed Dec. 12, 2013, which is hereby incorporated byreference in its entirety.

FIELD

The present invention relates to the field of multimedia security. Inparticular, the present invention provides a computer-implementedmethod, system, and computer readable medium for determining anillegitimate three dimensional video.

BACKGROUND

With the advancement in display technology, circuit design, and signalprocessing, it has become feasible to capture and render threedimensional (3D) videos on consumer platforms. A video is a sequence ofscenes and a scene is a sequence of images called frames. Threedimensional videos have been recognized as one of the essential parts ofnext-generation visual media. Three dimensional videos may berepresented using either stereo image recording (hereinafter may bereferred to as ‘SIR’) or depth-image-based rendering (hereinafter may bereferred to as ‘DIBR’). In SIR, left and right views for the same sceneare captured simultaneously using different camera positions. Althoughthe video is of a high quality, there are several drawbacks which limitits applicability in real-time applications. Firstly in SIR, both thecameras should have same parameters such as contrast, height, andbrightness. It is very difficult and costly to set both the cameras withsame parameters. DIBR, on the other hand, requires one center view andcorresponding depth map. Virtual left and right views are generated bymapping the center view with its corresponding depth map to providethree dimensional experiences. In contrast to SIR, it offers severaladvantages. Firstly, depth degree is adjustable in the DIBR systemswhich help the viewers to adjust the depth condition they prefer. As thedepth map is an 8-bit gray scale image, it requires less storage spaceand low transmission bandwidth. Further, center view video consists ofcolor frames and can be used independently as two dimensional video i.e.DIBR systems have backward compatibility with the widely used twodimensional systems.

The convergence of networks, devices, and services combined with thetechnological advancements in digital storage, multimedia compression,and miniaturization of digital cameras has led to an explosive growth ofonline video content. In addition to the professionally produced videocontent, user-generated content and content produced by hardcoreamateurs are also on the rise. Videos can easily be shared over theInternet using popular video sharing sites such as You Tube® and Yahoo!®Video. Three dimensional videos can be illegally distributed in multipleways, including, but not limited to, unauthorized distribution of boththe center video as well as depth video, unauthorized distribution ofcenter video and unauthorized distribution of either left or rightsynthesized view. Although the user experience is enhanced with the newmeans of content production, distribution, and monetization, it has madeillegal reproduction and distribution of digital content easier. Piracyof digital media content is increasing day by day and is a major causeof worry for the digital content owners. To protect the authenticity ofthree dimensional videos, a number of watermarking algorithms have beenproposed. Watermarking is the process of embedding a watermark into anobject such as a video which can be extracted later on from thesuspected files for proving the digital rights.

To protect the copyright of three dimensional videos, few watermarkingtechniques have been proposed. Although a number of techniques exist fortwo dimensional watermarking, the mechanism to create and render twodimensional videos cannot be extrapolated to three dimensional videossince the nature of three dimensional videos differ from that of twodimensional videos. Three dimensional videos have depth-image-basedrendering. DIBR videos have center view and depth map which aresynthesized to generate left and right views to provide 3D experience.Koz et al. has proposed a watermarking scheme for the copyrightprotection of SIR three dimensional videos. The method is able toextract the watermark from known and unknown camera positions. Haliciand Alatan have proposed a watermarking method for DIBR images. Awatermark is embedded in spatial domain with a weighting factor. Themethod may not be robust against non-linear transformations such asrotation. Algorithms such as Singular Value Decomposition (hereinaftermay be referred to as ‘SVD’) have gained importance due to itsrobustness to withstand attacks relative to algorithms such as DiscreteCosine Transform (hereinafter may be referred to as ‘DCT’) and DiscreteWavelet Transform (hereinafter may be referred to as ‘DWT’). Variousmethods have been proposed to watermark digital images using SVD.However, the application of SVD in watermarking of videos is difficult.This limitation exists primarily due to temporal nature of videos,presence of special effects in videos, and non-blind nature of SVD basedmethods.

SUMMARY

A method for determining an illegitimate three dimensional videoincludes generating by a video analyzing computing device a first sceneaveraged frame value for each of a plurality of scenes of an originalvideo and a second scene averaged frame value for each of a plurality ofscenes of a resembling video. Each of at least a subset of the scenes ofthe resembling video is mapped by the video analyzing computing deviceto a corresponding one of the scenes of the original video based on acomparison of at least a subset of the first scene averaged frame valuesand the second scene averaged frame values. A first singular value scorefor each of one or more frames of each of the subset of scenes of theresembling video and a second singular value score for each of one ormore frames of the corresponding one of the scenes of the original videois generated by the video analyzing computing device. One or morematching ones of the one or more frames of each of the at least a subsetof scenes of the resembling video is identified by the video analyzingcomputing device based on a comparison of at least a subset of the firstsingular value scores and the second singular value scores. A firstwatermark is extracted by the video analyzing computing device from theidentified matching frames.

A video analyzing computing device includes a processor and a memorycoupled to the processor which is configured to be capable of executingprogrammed instructions including and stored in the memory to generate afirst scene averaged frame value for each of a plurality of scenes of anoriginal video and a second scene averaged frame value for each of aplurality of scenes of a resembling video. Each of at least a subset ofthe scenes of the resembling video is mapped to a corresponding one ofthe scenes of the original video based on a comparison of at least asubset of the first scene averaged frame values and the second sceneaveraged frame values. A first singular value score for each of one ormore frames of each of the subset of scenes of the resembling video anda second singular value score for each of one or more frames of thecorresponding one of the scenes of the original video is generated. Oneor more matching ones of the one or more frames of each of the at leasta subset of scenes of the resembling video is identified based on acomparison of at least a subset of the first singular value scores andthe second singular value scores. A first watermark is extracted fromthe identified matching frames.

A non-transitory computer readable medium having stored thereoninstructions for testing a firewall includes executable code which whenexecuted by a processor, causes the processor to perform steps includinggenerating a first scene averaged frame value for each of a plurality ofscenes of an original video and a second scene averaged frame value foreach of a plurality of scenes of a resembling video. Each of at least asubset of the scenes of the resembling video is mapped to acorresponding one of the scenes of the original video based on acomparison of at least a subset of the first scene averaged frame valuesand the second scene averaged frame values. A first singular value scorefor each of one or more frames of each of the subset of scenes of theresembling video and a second singular value score for each of one ormore frames of the corresponding one of the scenes of the original videois generated. One or more matching ones of the one or more frames ofeach of the at least a subset of scenes of the resembling video isidentified based on a comparison of at least a subset of the firstsingular value scores and the second singular value scores. A firstwatermark is extracted from the identified matching frames.

This technology provides a number of advantages including providing moreefficient and effective methods, non-transitory computer readable media,and devices for determining an illegitimate three dimensional video. Inparticular, this technology more effectively extracts a watermark from apotentially illegitimate three dimensional video to allow comparisonwith that of an original video.

BRIEF DESCRIPTION OF THE DRAWINGS

Features, aspects, and advantages of the present invention will bebetter understood when the following detailed description is read withreference to the accompanying drawings, wherein:

FIG. 1 is a block diagram of a computing device to which this technologymay be applied according to an exemplary embodiment;

FIG. 2 is a block diagram illustrative of an exemplary process that canbe employed to render three dimensional videos;

FIG. 3 is illustrative of an exemplary method to embed a watermark in athree dimensional video;

FIG. 4 is a block diagram depicting exemplary scene mapping and framemapping;

FIG. 5 is illustrative of an exemplary method to map scenes and framesas a pre-requisite to extracting a watermark from a three dimensionalvideo; and

FIG. 6 is a flowchart illustrative of exemplary utility of thistechnology.

DETAILED DESCRIPTION

Disclosed embodiments provide computer-implemented method, system, andcomputer-readable media for determining illegitimate three dimensionalvideos with DIBR as rendering technology. While the particularembodiments described herein may illustrate the invention in aparticular domain, the broad principles behind these embodiments couldbe applied in other fields of endeavor. To facilitate a clearunderstanding of this technology, illustrative examples are providedherein which describe certain aspects of the disclosure. However, it isto be appreciated that these illustrations are not meant to limit thescope of the disclosure and are provided herein to illustrate certainconcepts associated with the disclosure.

The following description is full and informative description of thebest method and system presently contemplated for carrying out thistechnology which is known to the inventors at the time of filing thepatent application. Of course, many modifications and adaptations willbe apparent to those skilled in the relevant arts in view of thefollowing description in view of the accompanying drawings and theappended claims. While the systems and methods described herein areprovided with a certain degree of specificity, this technology may beimplemented with either greater or lesser specificity, depending on theneeds of the user. Further, some of the features of this technology maybe used to advantage without the corresponding use of other featuresdescribed in the following paragraphs.

Any headings used herein are for organizational purposes only and arenot meant to limit the scope of the description or the claims. As apreliminary matter, the definition of the term “or” for the purpose ofthe following discussion and the appended claims is intended to be aninclusive “or” That is, the term “or” is not intended to differentiatebetween two mutually exclusive alternatives. Rather, the term “or” whenemployed as a conjunction between two elements is defined as includingone element by itself, the other element itself, and combinations andpermutations of the elements. For example, a discussion or recitationemploying the terminology “A” or “B” includes: “A” by itself, “B” byitself and any combination thereof, such as “AB” and/or “BA.” As usedherein, the word “may” is used in a permissive sense rather than themandatory sense. Similarly, the words “include”, “including”, and“includes” mean including, but not limited to.

It is also to be understood that this technology may be implemented invarious forms of hardware, software, firmware, special purposeprocessors, or a combination thereof. Preferably, this technology isimplemented in software as a program tangibly embodied on a programstorage device. The program may be uploaded to, and executed by, amachine comprising any suitable architecture. One or more of theabove-described techniques may be implemented in or involve one or morecomputer systems.

FIG. 1 is a block diagram of a video analyzing computing device 100 towhich this technology may be applied according to an embodiment of thistechnology. The system includes at least one processor 102, designed toprocess instructions, for example computer readable instructions (i.e.,code) stored on a storage device 104. By processing instructions,processing device 102 may perform the steps and functions disclosedherein. Storage device 104 may be any type of storage device, forexample, but not limited to an optical storage device, a magneticstorage device, a solid state storage device and a non-transitorystorage device. The storage device 104 may contain an application 104 awhich is a set of instructions (i.e. code). Alternatively, instructionsmay be stored in one or more remote storage devices, for example storagedevices accessed over a network or the internet 106. The computingdevice 100 also includes an operating system and microinstruction code.The various processes and functions described herein may either be partof the microinstruction code or part of the program (or combinationthereof) which is executed via the operating system. Computing device100 additionally may have memory 108, an input controller 110, and anoutput controller 112 and communication controller 114. A bus (notshown) may operatively couple components of computing device 100,including processor 102, memory 108, storage device 104, inputcontroller 110 output controller 112, and any other devices (e.g.,network controllers, sound controllers, etc.). Output controller 112 maybe operatively coupled (e.g., via a wired or wireless connection) to adisplay device (e.g., a monitor, television, mobile device screen,touch-display, etc.) in such a fashion that output controller 112 cantransform the display on display device (e.g., in response to modulesexecuted). Input controller 110 may be operatively coupled (e.g., via awired or wireless connection) to input device (e.g., mouse, keyboard,touch-pad, scroll-ball, touch-display, etc.) in such a fashion thatinput can be received from a user. The communication controller 114 iscoupled to a bus (not shown) and provides a two-way coupling through anetwork link to the internet 106 that is connected to a local network116 and operated by an internet service provider (hereinafter referredto as ‘ISP’) 118 which provides data communication services to theinternet. Members or subscribers of social media may be connected to thelocal network 116. A network link typically provides data communicationthrough one or more networks to other data devices. For example, networklink may provide a connection through local network 116 to a hostcomputer, to data equipment operated by an ISP 118. A server 120 maytransmit a requested code for an application through internet 106, ISP118, local network 116 and communication controller 114. Of course, FIG.1 illustrates computing device 100 with all components as separatedevices for ease of identification only. Each of the components may beseparate devices (e.g., a personal computer connected by wires to amonitor and mouse), may be integrated in a single device (e.g., a mobiledevice with a touch-display, such as a smartphone or a tablet), or anycombination of devices (e.g., a computing device operatively coupled toa touch-screen display device, a plurality of computing devices attachedto a single display device and input device, etc.). Computing device 100may be one or more servers, for example a farm of networked servers, aclustered server environment, or a cloud network of computing devices.

A three dimensional DIBR video is essentially represented as video anddepth. This format is eye-catching as inclusion of depth enables displayindependent solution for three dimensional that supports generation ofan increased number of views, which may be required by different threedimensional displays. In DIBR video, depth data tells about the distanceof the objects from the camera in the three dimensional view. DIBRsystems wrap the center video data frame according to the valuescontained in the depth frame and fill the holes to synthesize left-eyeand right-eye virtual views. Depth frames are pre-processed in order togenerate more natural virtual views.

FIG. 2 is a block diagram illustrative of a process that can be employedto render three dimensional videos. The depth channel of a threedimensional video is pre-processed 202. Pre-processing 202 of depthchannel is done to reduce the large holes so as to maintain the qualityof virtually synthesized left and right views. The next step is theframe wrapping 204 which aims at generating the virtual left and rightviews by mapping the pixels of center video frame to the correspondingdepth frame. The pixels in depth video frame range from Z_(near) toZ_(far), where Z_(near) and Z_(far) denotes the nearest and farthestplanes in the 3D view. For an 8-bit depth map, the pixel value rangesfrom 0 to 255. The pixels of depth map are mapped with pixels of centervideo frame using below equations.

$\begin{matrix}{x_{L} = {x_{C} + \left( {\frac{t_{x}}{2} \times \frac{f}{z}} \right)}} & {{Equation}.\mspace{14mu} I} \\{x_{R} = {x_{c} - \left( {\frac{t_{x}}{2} \times \frac{f}{z}} \right)}} & {{Equation}.\mspace{14mu}{II}}\end{matrix}$

where x_(C), and x_(R), are x_(L) the x-coordinate of the pixels in thecenter frame (F_(C)), synthesized right frame (F_(VR)) and synthesizedleft frame (F_(VL)) respectively. f is the focal length, t_(x) is thebaseline distance and Z is the value of the pixel indepth video frame(D_(C)) corresponding to center video frame pixel.

According to the visibility property of a three dimensional frame, theobjects which are near will occlude the distant objects. Hence, farthestdepth value pixels are wrapped first.

When center video frame is wrapped with corresponding depth frame, holesor disocclusions are revealed. Neither center video frame norcorresponding depth video frame contains any texture information aboutthe holes or disocclusion area. To fill these newly exposed areas, holefilling 206 is applied using either an average filter or aninterpolation. Known methods, for example, linear interpolation may beapplied for filling the holes or disocclusions.

Disclosed systems and methods treat center video and depth asindependent channels for the purpose of watermarking. It is assumed thatany modification or alteration with the center video information willhave similar impact on the depth information. Watermark is embeddedindependently in center video as well as depth video by employing anon-blind video watermarking algorithm such as SVD. SVD is a linearalgebraic technique which optimally decomposes matrices to represent amaximum amount of signal energy in as few coefficients as possible.While using the SVD transformation a matrix is decomposed into threematrices U, S, and V. U and V are the orthogonal matrices and S is adiagonal matrix. The SVD is a technique that can be used in imagecompression techniques, but can also be applied to watermarking. The SVDis performed, after which the singular values are usually modified toembed the watermark. A pseudo-inverse SVD is then applied to obtain theoriginal content. The proposed method specifically employs S componentfor embedding watermark in each channel. Video consists of severalscenes and each scene consists of several frames. As the watermarkingprocess is non-blind, an efficient mapping process is proposed to avoidsuch synchronization issues. Frames of the original video are mappedwith the resembling video before extracting the watermark. The proposedmethod uses scene based mapping process at the watermark extractor sideto map the possibly resembling frames with the original frames. Thefirst step is watermark embedding procedure and the next step iswatermark extracting procedure.

FIG. 3 is illustrative of an exemplary SVD-based watermarking method 300to embed a watermark in a three dimensional video 302. For embedding thewatermark, SVD of the center video frame, F_(C) ^(N×M), andcorresponding depth frame, D_(C) ^(N×M), is computed 304 as:F _(C) =U _(C) S _(C) V _(C) ^(T)  Equation IIID _(C) =U _(D) S _(D) V _(D) ^(T)  Equation IV

where:

U_(C) and V_(C) are the orthogonal matrices of center video frame F_(C)of three dimensional video 302

S_(C) is the diagonal matrix of center video frame F_(C) of threedimensional video 302

U_(D) and V_(D) are the orthogonal matrices of depth frame D_(C) ofthree dimensional video 302

S_(D) is the diagonal matrix of corresponding depth frame D_(C) of threedimensional video 302

The watermark W^(n×m) 306 is obtained and its SVD is computed 308 as:W=U _(w) S _(w) V _(w) ^(T)  Equation V

where

U_(w) and V_(w) are the orthogonal matrices of watermark W

S_(w) is the diagonal matrix of watermark W.

The watermark W^(n×m) is embedded 310 inside the center video frameF_(C) ^(N×M) and corresponding depth frame D_(C) ^(N×M) to obtainwatermarked center video frame F_(WC) ^(N×M) and depth D_(WC) ^(N×M)frames 312 as:F _(WC) =U _(C)(S _(C) +α×S _(w))V _(C) ^(T) =U _(C) S _(WC) V _(C)^(T)  Equation VID _(WC) =U _(D)(S _(D) +β×S _(w))V _(D) ^(T) =U _(D) S _(WD) V _(D)^(T)  Equation VII

Where:

α and β represents the watermark embedding strength in center videoframe and corresponding depth frame respectively. Watermarked centervideo F_(WC) and depth video D_(WC) are then rendered using the methoddiscussed in FIG. 2 to obtain the synthesized left and right videorespectively.

FIG. 4 in conjunction with FIG. 5 is a block diagram depicting the sceneand frame mapping process. For non-blind and semi-blind watermarkingmethods, method to map the scenes and frames is a pre-requisite in orderto extract the watermark from a three dimensional watermarked video. Anyaddition or deletion of scene will lead to change in the order of thescenes. To avoid such synchronization issues, an efficient mappingprocess is required to map the frames of original video 302 with theresembling video 402. A scene based approach has been used for mappingthe resembling frames with the original frames. Depth frame carries onlydistance information about the objects which are present in the centervideo frame while center video frame carries most information such astexture information about the three dimensional view. According to anembodiment of this technology, center video frames are used fordetecting the scenes. Scenes of both the original three dimensionalcenter video 302 and the possibly resembling three dimensional centervideo 402 may be detected using known scene detection methodologies. Therespective videos are read and scenes are detected 404, 406. A scenechange detection algorithm is applied to determine the number of scenesin the video 408, 412. Known scene change detection may be applied.Preferably, scene change detection method disclosed in patentapplication titled ‘System for Scene Based Video Watermarking andMethods thereof’ may be employed. Assume that there are n and n′ scenesin the original video 408, 410 and resembling video 412, 414respectively. A scene averaged frame 410 is used as a unique sceneidentifier for scene mapping. However, other unique identifiers such asDiscrete Cosine Transforms (DCT) coefficients may be used. The term,scene averaged frame, as used herein, means an average of thecorresponding pixels of all the frames in a given scene. Let us supposethat F_(avg) 410, 502 and F′_(avg) 414, 506 be the scene averaged framesof original 302 and resembling center video respectively 402. The scenesin each of the original video and the resembling video is detected andmapped against each other. The scene averaged image of the first sceneof the resembling video 506 is compared with scene averaged image ofeach scene of the original video 508. If the difference 416 betweenscene averaged frame of a scene of the original video and that of theresembling video is lesser or equivalent to a preconfigured thresholdvalue 510, then the two scenes are the same or a close match 514. If thevalue is more than the threshold value then the two scenes may beconsidered as different scenes 512. This process is repeated until thelast scene of the original video 516, 538. The set of mapped scenes canbe examined further for frame mapping. Frames from scenes of theoriginal video 520 are compared with frames from corresponding mappedscenes of the resembling video 522. Singular values are computed usingSVD for each frame of the mapped scenes 524, 526. The frames F_(AC)^(M′×N′) of the mapped scenes of the resembling video are decomposedinto one singular matrix S_(AC) ^(N′×M′) and two orthogonal matrices−U_(AC) ^(N′×M′) and V_(AC) ^(M′×M′) as:F _(AC) =U _(AC) S _(AC) V _(AC) ^(T)  Equation VIII

Compute the difference 416, 528, 530 between the singular values ofresembling frame S_(AC) with the singular values of original framesS_(C) as:diff=(Σ|S _(AC) −S _(C)(1)|, . . . ,Σ|S _(AC) −S _(C)(t)|)  Equation IX

where:

t denotes the number of frames in the corresponding scene of originalvideo 302.

The resembling frame for which the difference is minimum with theoriginal frame will be the matching frame 418, 532. This is repeateduntil each frame of the resembling video is mapped with each frame ofthe original video 534, 536. Frames in resembling video with nocorresponding frame match in corresponding scene of original video arediscarded 538. Now, the frames have been mapped and the watermark can beextracted from the mapped frames of the resembling video. Suspectedvideo files could be: (i) center video and corresponding depth video,(ii) center video, (iii) synthesized left view video, and (iv)synthesized right view video. Watermark is extracted from thesesuspected files as:

$\begin{matrix}{W_{C}^{\prime} = {{U_{W}\left( \frac{S_{AC} - S_{C}}{\alpha} \right)}V_{W}^{T}}} & {{Equation}\mspace{14mu} X} \\{W_{D}^{\prime} = {{U_{W}\left( \frac{S_{AD} - S_{C}}{\beta} \right)}V_{W}^{T}}} & {{Equation}\mspace{14mu}{XI}} \\{W_{L}^{\prime} = {{U_{W}\left( \frac{s_{AL} - s_{C}}{\alpha} \right)}V_{W}^{T}}} & {{Equation}\mspace{14mu}{XII}} \\{W_{R}^{\prime} = {{U_{W}\left( \frac{s_{AR} - s_{C}}{\alpha} \right)}V_{W}^{T}}} & {{Equation}\mspace{14mu}{XIII}}\end{matrix}$

where

S_(AC), S_(AD), S_(AL), and S_(AR) are the singular values of theresembling center video frame, corresponding depth frame, synthesizedleft view video frame and synthesized right view video framerespectively.

W′_(C), W′_(D), W′_(L), and W′_(R) are the watermarks extracted from thecenter video frame, depth video frame, synthesized left view videoframe, and synthesized right view video frame respectively.

FIG. 6 is a flowchart illustrative of exemplary utility of thistechnology. A video 302, which is captured by a camera 602 may beprocessed inside a video processing laboratory 604. The video 302created for an intended purpose is watermarked with the watermarkinformation for example, owner's information. A watermark is a visible,or preferably invisible, identification data that is permanentlyembedded in the digital data, that is, it remains present within thedata after any encoding and decoding process. The embedded watermarkinformation can be recovered from the unauthorized copy which is createdby imitating the watermarked video and can be used for protecting thedigital right violations. The watermarked video 314 may be availablethrough multiple channels to an end-user through a communication network606 or in the form of a physical media 608 as the case maybe. In case ofdownloading video from Internet, a download request is sent from acomputer to Internet for a video. The download reaches the Web serverthrough a network. The Web server may be operatively connected to aserver with an application 104 a. An end-user downloads the video andmay distribute this video to unauthorized consumers. Any suspect copy ofa video may be validated for its authenticity to determine if it is anillegal copy by extracting the watermark information. The extractedwatermark 610 contains the watermark information which can be used toestablish digital rights.

Having thus described the basic concept of the invention, it will berather apparent to those skilled in the art that the foregoing detaileddisclosure is intended to be presented by way of example only, and isnot limiting. Various alterations, improvements, and modifications willoccur and are intended to those skilled in the art, though not expresslystated herein. These alterations, improvements, and modifications areintended to be suggested hereby, and are within the spirit and scope ofthe invention. Additionally, the recited order of processing elements orsequences, or the use of numbers, letters, or other designationstherefore, is not intended to limit the claimed processes to any orderexcept as may be specified in the claims. Accordingly, the invention islimited only by the following claims and equivalents thereto.

What is claimed is:
 1. A method for determining an illegitimate threedimensional video, the method comprising: generating by a videoanalyzing computing device a first scene averaged frame value for eachof a plurality of scenes of an original video and a second sceneaveraged frame value for each of a plurality of scenes of a resemblingvideo; mapping by the video analyzing computing device each of at leasta subset of the scenes of the resembling video to a corresponding one ofthe scenes of the original video based on a comparison of at least asubset of the first scene averaged frame values and the second sceneaveraged frame values; generating by the video analyzing computingdevice a first singular value score for each of one or more frames ofeach of the subset of scenes of the resembling video and a secondsingular value score for each of one or more frames of the correspondingone of the scenes of the original video; identifying by the videoanalyzing computing device one or more matching ones of the one or moreframes of each of the at least a subset of scenes of the resemblingvideo based on a comparison of at least a subset of the first singularvalue scores and the second singular value scores; and extracting by thevideo analyzing computing device a first watermark from the identifiedmatching frames.
 2. The method of claim 1, further comprisingdetermining by the video analyzing computing device when the resemblingvideo is illegitimate based on a comparison of the first watermark to asecond watermark associated with the original video.
 3. The method ofclaim 1, wherein each of the at least a subset of the scenes of theresembling video is mapped to the corresponding one of the scenes of theoriginal video when a difference between the respective first and secondscene averaged frame values is less than a predetermined threshold. 4.The method of claim 1, wherein the identified matching frames of theresembling video each have an associated first singular value score thatis least different than one of the second singular value scoresassociated with one of the frames in the respective corresponding one ofthe scenes of the original video.
 5. The method of claim 1, furthercomprising displaying by the video analyzing computing device at leastthe identified matching frames.
 6. A video analyzing computing device,comprising a processor and a memory coupled to the processor which isconfigured to be capable of executing programmed instructions comprisingand stored in the memory to: generate a first scene averaged frame valuefor each of a plurality of scenes of an original video and a secondscene averaged frame value for each of a plurality of scenes of aresembling video; map each of at least a subset of the scenes of theresembling video to a corresponding one of the scenes of the originalvideo based on a comparison of at least a subset of the first sceneaveraged frame values and the second scene averaged frame values;generate a first singular value score for each of one or more frames ofeach of the subset of scenes of the resembling video and a secondsingular value score for each of one or more frames of the correspondingone of the scenes of the original video; identify one or more matchingones of the one or more frames of each of the at least a subset ofscenes of the resembling video based on a comparison of at least asubset of the first singular value scores and the second singular valuescores; and extract a first watermark from the identified matchingframes.
 7. The video analyzing computing device of claim 6, wherein theprocessor coupled to the memory is further configured to be capable ofexecuting at least one additional programmed instruction comprising andstored in the memory to determine when the resembling video isillegitimate based on a comparison of the first watermark to a secondwatermark associated with the original video.
 8. The video analyzingcomputing device of claim 6, wherein each of the at least a subset ofthe scenes of the resembling video is mapped to the corresponding one ofthe scenes of the original video when a difference between therespective first and second scene averaged frame values is less than apredetermined threshold.
 9. The video analyzing computing device ofclaim 6, wherein the identified matching frames of the resembling videoeach have an associated first singular value score that is leastdifferent than one of the second singular value scores associated withone of the frames in the respective corresponding one of the scenes ofthe original video.
 10. The video analyzing computing device of claim 6,wherein the processor coupled to the memory is further configured to becapable of executing at least one additional programmed instructioncomprising and stored in the memory to display at least the identifiedmatching frames.
 11. A non-transitory computer readable medium havingstored thereon instructions for testing a firewall comprising executablecode which when executed by a processor, causes the processor to performsteps comprising: generating a first scene averaged frame value for eachof a plurality of scenes of an original video and a second sceneaveraged frame value for each of a plurality of scenes of a resemblingvideo; mapping each of at least a subset of the scenes of the resemblingvideo to a corresponding one of the scenes of the original video basedon a comparison of at least a subset of the first scene averaged framevalues and the second scene averaged frame values; generating a firstsingular value score for each of one or more frames of each of thesubset of scenes of the resembling video and a second singular valuescore for each of one or more frames of the corresponding one of thescenes of the original video; identifying one or more matching ones ofthe one or more frames of each of the at least a subset of scenes of theresembling video based on a comparison of at least a subset of the firstsingular value scores and the second singular value scores; andextracting a first watermark from the identified matching frames. 12.The non-transitory computer readable medium of claim 1, further havingstored thereon at least one additional instruction that when executed bythe processor cause the processor to perform at least one additionalstep comprising determining when the resembling video is illegitimatebased on a comparison of the first watermark to a second watermarkassociated with the original video.
 13. The non-transitory computerreadable medium of claim 11, wherein each of the at least a subset ofthe scenes of the resembling video is mapped to the corresponding one ofthe scenes of the original video when a difference between therespective first and second scene averaged frame values is less than apredetermined threshold.
 14. The non-transitory computer readable mediumof claim 11, wherein the identified matching frames of the resemblingvideo each have an associated first singular value score that is leastdifferent than one of the second singular value scores associated withone of the frames in the respective corresponding one of the scenes ofthe original video.
 15. The non-transitory computer readable medium ofclaim 11, further having stored thereon at least one additionalinstruction that when executed by the processor cause the processor toperform at least one additional step comprising displaying at least theidentified matching frames.